Abstract: The common approach for artery-vein separation applies a presaturation pulse to obtain different image intensity representations in MRA data for arteries and veins. However, when arteries and veins do not run in opposite directions as in the brain, lungs, and heart, this approach fails. This paper presents an image processing approach devised for artery-vein separation. The anatomic separation utilizes fuzzy connected object delineation. The first step of this separation method is the segmentation of the entire vessel structure from the background via absolute connectedness by using scale-based affinity. The second step is to separate artery from vein via relative connectedness. After 'seed' points are specified inside artery and vein in the vessel- only image, the operation is performed in an iterative fashion. The small regions of the bigger aspects of artery and vein are separated in the initial iteration. Further regions are added with the subsequent iterations so that the small aspects of artery and vein are included in alter iterations. Shell rendering is used for 3D display. Combining the strengths of fuzzy connected object definition, object separation, and shell rendering, high- quality volume rendering of vascular information in MRA data has been achieved. MS-325 contrast-enhanced MRA were used to illustrate this approach. Several examples of 3D display of arteries and veins are included to show the considerable promise of this new approach. !14
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